The PhD (Pretty Helpful Development functions for) face recognition toolbox is a collection of Matlab functions and scripts intended to help researchers working in the field of face recognition. The toolbox was produced as a byproduct of my research work and is freely available for download.
The PhD toolbox features implementations of several popular face recognition techniques, such as principal component analysis, linear discriminant analysis, kernel principal component analysis, or kernel fisher analysis. In addition to these techniques, it contains functions for Gabor filter construction, Gabor feature extraction, phase congruency computation and others. An important part of the toolbox are also the evaluation tools that allow for the construction of the most common performance curves (e.g., ROC, DET, CMC, EPC) used for evaluating face recognition systems.
In addition to the above, the toolbox also features a large number of demo scripts that demonstrate how to use the functions from the toolbox in face recognition experiments using a real database. These scripts demonstrate the complete procedure of building and testing face recognition systems based on Gabor filters and subspace projection techniques.
You would need to go through the ROC cruve data and find the points you are looking for. The functions currently do not return these values, as they are usually not used for face recognition.
Hi, thank you
Can you also tell me how to calculate value of FMR1000 and ZeroFMR
Hi Prachi. You can use most of the functions of the toolbox with any modality. Depend on what you want to do though.
can we use this toolbox for fingerprint result analysis part.If we have normalize impostor and genuine distribution
THIS IS A GREAT WORK! WE APPRECIATE!
very helpful toolbox. thanks a lot
A great package. And Vito is a great adviser. Thank you.
Package needs a m file called normrc from the Neural Networks toolbox. But you can obtain it from other sources or write one yourself.
great tool box...
Awesome toolbox, the name tells the story
Great toolbox and even better documentation!